Fluctuating hydrodynamics of multicomponent membranes with embedded proteins

Camley, Brian A.; Brown, Frank L. H.

doi:10.1063/1.4892802

Cited by 31 publications

(27 citation statements)

References 135 publications

(215 reference statements)

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“…We expect that it remains the case for κ 0, considering that, as far as examined, the magnitudes of the expansion coefficients are correlated with each other through the recurrence relations. Our results qualitatively agree with one of the results of Camley and Brown [39] showing that the effect on a rigid disk should be negligibly small. The results were obtained with the aid of the immersed boundary method [59], where the boundary condition at the perimeter is altered from the no-slip condition.…”

Section: Discussionsupporting

confidence: 91%

Drag Coefficient of a Circular Inclusion in a Near-Critical Binary Fluid Membrane

Tani

Fujitani

2018

J. Phys. Soc. Jpn.

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We calculate the drag coefficient of a circular liquid domain, which is put in a flat fluid membrane composed of a binary fluid mixture lying in the homogeneous phase near the demixing critical point. Assuming a sufficiently small correlation length, we regard the domain dynamics as independent of the critical fluctuation and use the Gaussian free-energy functional for the mixture. Because of the near-criticality, the preferential attraction between the domain component and one of the mixture components generates the composition gradient outside the domain significantly and can affect the drag coefficient. We first consider a domain having the same membrane viscosity as the domain exterior. The drag coefficient is expanded with respect to a dimensionless strength of the preferential attraction. It is numerically shown that the magnitude of the expansion coefficient decreases much as the order of the strength increases and that the first-order term of the series usually gives a good approximation for practical material constants. The effect of the preferential attraction is shown to be able to become significantly large in practice. We second consider cases where the membrane viscosities of the domain interior and exterior are different. The first-order term of the expansion series decreases to approach zero as the domain viscosity increases to infinity. This agrees with previous numerical results showing that the hydrodynamics makes the effect of the preferential attraction negligibly small for a rigid disk. *

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Section: Discussionsupporting

confidence: 91%

Drag Coefficient of a Circular Inclusion in a Near-Critical Binary Fluid Membrane

Tani

Fujitani

2018

J. Phys. Soc. Jpn.

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“…Finally, if a protein distorts the surrounding membrane, additional drag may be caused, reducing the protein's diffusion coefficient. [66][67][68][69][70] If these effects are strong enough, they could potentially compete with or even overwhelm the hydrodynamic contributions to D discussed in this work.…”

Section: The Saffman-delbrück Model Is a Hydrodynamic Modelmentioning

confidence: 99%

“…In computing membrane-protein mobility, the flows are very longranged because of the underlying force monopole. Properties controlled by higher-order force moments (e.g., rotational diffusion, 18 domain relaxation, 38 or increased intrinsic viscosity 21,70 ) are expected to be less sensitive to finite system sizes.…”

Section: The Saffman-delbrück Model Is a Hydrodynamic Modelmentioning

confidence: 99%

Strong influence of periodic boundary conditions on lateral diffusion in lipid bilayer membranes

Camley

Lerner

Pastor

et al. 2015

The Journal of Chemical Physics

Self Cite

125

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The Saffman-Delbrück hydrodynamic model for lipid-bilayer membranes is modified to account for the periodic boundary conditions commonly imposed in molecular simulations. Predicted lateral diffusion coefficients for membrane-embedded solid bodies are sensitive to box shape and converge slowly to the limit of infinite box size, raising serious doubts for the prospects of using detailed simulations to accurately predict membrane-protein diffusivities and related transport properties. Estimates for the relative error associated with periodic boundary artifacts are 50% and higher for fully atomistic models in currently feasible simulation boxes. MARTINI simulations of LacY membrane protein diffusion and LacY dimer diffusion in DPPC membranes and lipid diffusion in pure DPPC bilayers support the underlying hydrodynamic model. C 2015 AIP Publishing LLC. [http://dx

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“…Recent examples of the supra-coarse-grained approach include simulations of large-scale membrane remodelling by Bin-amphiphysin-Rvs (BAR) domains (Cui et al, 2013;Simunovic et al, 2013;Yu and Schulten, 2013), the membrane-induced formation of peptide fibrils (Morriss-Andrews et al, 2014) and the supra-molecular organization of photosynthetic membranes (Lee et al, 2015). Furthermore, the supra-coarse-grained approach allows for a natural connection to the macroscopic scale using, for instance, field-theory-or fluid-dynamics-based descriptions of cell membranes (Ayton et al, 2009;Camley and Brown, 2014;Fedosov et al, 2014;Yolcu et al, 2014).…”

Section: Supra Coarse-grain Resolutionmentioning

confidence: 99%

Computational ‘microscopy’ of cellular membranes

Ingólfsson

Arnarez²,

Periole³

et al. 2016

Journal of Cell Science

136

120

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Computational 'microscopy' refers to the use of computational resources to simulate the dynamics of a molecular system. Tuned to cell membranes, this computational 'microscopy' technique is able to capture the interplay between lipids and proteins at a spatiotemporal resolution that is unmatched by other methods. Recent advances allow us to zoom out from individual atoms and molecules to supramolecular complexes and subcellular compartments that contain tens of millions of particles, and to capture the complexity of the crowded environment of real cell membranes. This Commentary gives an overview of the main concepts of computational 'microscopy' and describes the state-of-the-art methods used to model cell membrane processes. We illustrate the power of computational modelling approaches by providing a few in-depth examples of largescale simulations that move up from molecular descriptions into the subcellular arena. We end with an outlook towards modelling a complete cell in silico.

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Fluctuating hydrodynamics of multicomponent membranes with embedded proteins

Cited by 31 publications

References 135 publications

Drag Coefficient of a Circular Inclusion in a Near-Critical Binary Fluid Membrane

Drag Coefficient of a Circular Inclusion in a Near-Critical Binary Fluid Membrane

Strong influence of periodic boundary conditions on lateral diffusion in lipid bilayer membranes

Computational ‘microscopy’ of cellular membranes

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